CN114062109B - Rock damage acoustic emission secondary main frequency identification extraction method - Google Patents
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Abstract
The invention relates to a rock destruction acoustic emission secondary main frequency identification extraction method. According to the invention, standard cylinder samples of rocks with different geological factors are prepared, acoustic emission sensors are uniformly arranged on the side surfaces along the circumferential direction, a uniaxial compression experiment is carried out, and the acoustic emission sensors receive original acoustic emission waveforms which are released when the rock samples are started to be loaded to be completely destroyed in the whole process; sequentially denoising an original acoustic emission waveform and performing fast Fourier transform to obtain a two-dimensional spectrogram, and performing fuzzification treatment to obtain a fuzzified two-dimensional spectrogram; capturing and identifying an acoustic emission signal with a secondary primary frequency characteristic, and extracting an acoustic emission primary frequency and a secondary primary frequency of the acoustic emission signal; acquiring acoustic emission signals of different lithology samples from the beginning of loading to the complete destruction of the whole process to obtain acoustic emission signal frequency domain data of each moment of rock damage destruction, judging the type of the acoustic emission signal for the acoustic emission signal with secondary main frequency characteristics, calculating the center frequency, and describing the destruction mode by combining the sample destruction load-time curve.
Description
Technical Field
The invention relates to a rock destruction acoustic emission secondary main frequency identification extraction method, and belongs to the technical field of rock destruction mode identification.
Background
The breaking of rock material under load is a complex progressive process. Before macroscopic fracture, the inside of the sample has the multi-characteristic microscopic fracture phenomenon, and at least two or more fracture mechanisms of stretching fracture and shearing sliding exist in the fracture process. When different damage modes occur in the rock, corresponding elastic energy is induced to be released, elastic waves with different characteristics are generated, and acoustic emission signals received by the detection sensor are formed. The acoustic emission technology is an effective method for monitoring the inoculation, the expansion and the aggregation of micro-damage events in the rock disaster process in real time by utilizing transient elastic wave information generated by internal fracture and damage of the rock in the loading process and continuously monitoring and testing the damage progress of the material in the whole loading process so as to research rich information such as the stress state, the damage mode, the physical and mechanical properties, the combination characteristics of the rock and the like.
However, the existing acoustic emission technology has insufficient utilization rate of acoustic emission signals, usually only uses simplified characteristic parameters of waveforms or concentrates research objects on acoustic emission main frequency evolution characteristics and frequency band duty ratio relation thereof, has insufficient consideration on diversity and global property of acoustic emission intrinsic frequency domains, is easy to lose important information, is difficult to form accurate quantitative evaluation, and is difficult to realize effective rock damage mechanism analysis.
Disclosure of Invention
Aiming at the defects of the existing method for analyzing the rock failure mode through acoustic emission frequency domain information, the method for identifying and extracting the secondary main frequency of the rock failure acoustic emission is provided, and the rock failure mode can be judged more accurately.
A rock destruction acoustic emission secondary main frequency identification extraction method comprises the following specific steps:
(1) Preparing rocks with different geological factors into standard cylinder samples;
(2) Acoustic emission sensors are uniformly arranged on the side surface of the cylindrical sample along the circumferential direction;
(3) Carrying out a uniaxial compression experiment on a cylindrical sample by adopting a rock mechanical testing machine, wherein an acoustic emission sensor receives an original acoustic emission waveform which is released when the rock sample starts to be loaded to be completely destroyed in the whole process in the experimental process;
(4) Denoising the original acoustic emission waveform, and then performing fast Fourier transform to obtain a two-dimensional spectrogram;
(5) Carrying out blurring processing on amplitude and frequency data in the two-dimensional spectrogram to obtain a blurring two-dimensional spectrogram;
(6) Capturing and identifying an acoustic emission signal with a secondary primary frequency characteristic, and extracting an acoustic emission primary frequency and a secondary primary frequency of the acoustic emission signal;
(7) Acquiring acoustic emission signals of different lithology samples from the beginning of loading to the complete destruction of the whole process, obtaining acoustic emission signal frequency domain data of each moment of rock damage destruction, judging the type of the acoustic emission signals according to the distribution characteristics of the main frequency and the secondary main frequency of the acoustic emission signals with the characteristic of the secondary main frequency, calculating the center frequency of each type of signals, and describing the destruction mode of the whole rock destruction process by combining the sample destruction load-time curve;
the rock with different geological factors in the step (1) comprises a magma rock, sedimentary rock and metamorphic rock, granite is used as a magma rock sample, sandstone is used as a sedimentary rock sample, and marble is used as a metamorphic rock sample;
the size of the sample is a standard cylinder with the diameter phi 50mm multiplied by the height H100 mm; the non-parallelism error of the two end surfaces of the sample is less than 0.05mm; the two end faces of the sample are perpendicular to the axis, and the deviation is smaller than 0.25 degrees; the error of the diameter of the sample along the height is less than 0.3mm;
the acoustic emission sensor on the side surface of the cylinder sample in the step (2) is axially arranged with upper and lower layers along the cylinder sample, the distance between the acoustic emission sensor on the upper layer and the top end of the cylinder sample is 1/8-3/8 of the height of the cylinder sample, and the distance between the acoustic emission sensor on the lower layer and the bottom end of the cylinder sample is 1/8-3/8 of the height of the cylinder sample;
preferably, the number of the acoustic emission sensors is 8, the number of the acoustic emission sensors on the upper layer is 4, the distance between the acoustic emission sensors on the upper layer and the top end of the cylindrical sample is 1/4 of the height of the cylindrical sample, and the distance between the acoustic emission sensors on the lower layer and the bottom end of the cylindrical sample is 1/4 of the height of the cylindrical sample;
the loading mode of the uniaxial compression experiment in the step (3) is axial displacement closed-loop control: firstly, applying a load of 0.5kN to a sample, and after the pressure-bearing end of the sample is fully contacted with a press, synchronizing the sampling time of a rock mechanical testing machine and an acoustic emission signal acquisition system, and continuously applying an axial load at a rate of 0.2mm/min until the sample is completely destroyed; the acoustic emission signal acquisition system sets sampling frequency: 1000kHz, sample length: 2048, threshold: 40dB, gain of forward: 40dB;
the denoising treatment in the step (4) is a wavelet threshold denoising method;
furthermore, the wavelet threshold denoising method adopts db3 wavelet basis and adopts soft threshold function and rigrsure threshold rule.
The two-dimensional spectrum information after the fast Fourier transform in the step (4) is that
S 0 ＝[(f 1 ,a 1 ),(f 2 ,a 2 ),…,(f p ,a p ),…,(f n ,a n )]
Wherein: s is S 0 -spectral information, f-nyquist frequency, a-amplitude, p-peak point, n-frequency domain data total;
the blurring processing method in the step (5) is as follows
1) S is selected 0 The medium amplitude value simultaneously satisfies a p ＞a p-1 And a p ＜a p+1 Peak point (f) of (p.gtoreq.2) condition p ,a p ) Sequentially store S 1 Through S 1 Mapping to obtain a blurred I spectrum diagram
Wherein: s is S 1 -blurring of i spectral information, f p -blurring of I peak frequency, a p -blur i peak amplitude, p-blur i peak, n-blur i frequency domain data total.
2) S is selected 1 The medium amplitude value simultaneously satisfies a p ＞a p-1 And a p ＜a p+1 Peak point (f) of (p.gtoreq.2) condition p ,a p ) Sequentially store S 2 Through S 2 Drawing to obtain a fuzzy II spectrogram
Wherein: s is S 2 -blurring of ii spectral information, f pp -fuzzification of the peak frequency, a, of the ii pp -peak amplitude of blurred ii, peak p-blurred ii, total number of n-blurred ii frequency domain data。
The main frequency and secondary main frequency characteristic identification and extraction method in the step (6) is as follows
1) Determining peak searching criterion, i.e. capturing peak value and peak position, searching mutually independent peak points in the blurred II spectrogram, and determining peak value and peak position point (f ppp ,a ppp ) Deposit S 3 ；
2) Through S 3 Drawing a rasterized extremum diagram by medium data, selecting a peak position corresponding to the highest peak value and a peak position corresponding to the next highest peak value in the rasterized extremum diagram, and calculating a ratio R of the next highest peak value to the highest peak value
Wherein: a, a sub-max Sub-peak amplitude, a max -a highest peak amplitude;
3) If R is less than 80%, the signal is marked as a signal without secondary main frequency characteristics, and can not be used for judging the rock destruction mode; if R is greater than 80%, the highest peak amplitude in the grid extremum chart is marked as the main frequency amplitude of the acoustic emission signal, and the frequency corresponding to the highest peak amplitude is the main frequency of the signal; the secondary peak amplitude is the secondary main frequency amplitude of the signal, and the frequency corresponding to the secondary peak amplitude is the secondary main frequency of the signal;
method for judging type and destruction mode of acoustic emission signal
1) For the acoustic emission signal with the secondary primary frequency characteristic, calculating a frequency interval formed by the primary frequency and the secondary primary frequency value of the acoustic emission signal;
2) Dividing the frequency interval into two equal parts by utilizing a frequency dividing line, wherein the frequency at the dividing line is defined as the frequency of the dividing line;
3) The signals with the primary frequency and the secondary primary frequency not smaller than the boundary frequency are regarded as H-H type double high frequency signals, the signals with the primary frequency and the secondary primary frequency smaller than the boundary frequency are regarded as L-L type double low frequency signals, and the signals with the primary frequency larger than the boundary frequency and the secondary primary frequency smaller than the boundary frequency or the signals with the primary frequency smaller than the boundary frequency and the secondary primary frequency larger than the boundary frequency are regarded as H-L type mixed frequency signals;
4) The double high frequency signals correspond to shear damage, the double low frequency signals correspond to stretch-draw damage, and the mixed frequency signals correspond to stretch-shear composite damage;
5) The center frequencies of the H-H type signal, the L-L type signal and the H-L type signal are calculated respectively, the damage evolution process (sample damage time-load curve) of the whole loading process of each rock sample is divided into 3 stages according to the axial stress-strain relation of each rock sample, the stages are compaction to elastic deformation stage (stage I), micro-crack stable development stage (stage II) and crack expansion to damage stage (stage III) in sequence, and the damage mode of the whole rock damage process is described by combining the sample damage load-time curve.
The beneficial effects of the invention are as follows:
(1) Compared with the existing frequency domain analysis method, the rock destruction acoustic emission secondary main frequency identification extraction method has the advantages of high operation speed, high result accuracy, flexible frequency domain data processing and the like, can output parameters such as acoustic emission main frequency, acoustic emission secondary main frequency and corresponding amplitude of acoustic emission main frequency of single designated time and position waveform, and can also output acoustic emission signal frequency domain analysis statistical results of a certain stage or the whole test process;
(2) Compared with the existing frequency domain analysis method, the method fully considers the multiple information contained in the two-dimensional spectrogram, improves the accuracy of identifying the acoustic emission secondary main frequency, eliminates the influence of artificial subjective discrimination, and provides a new thought for quantitative evaluation of the rock failure mode by combining the acoustic emission secondary main frequency with the acoustic emission main frequency and jointly applying the acoustic emission secondary main frequency to the description of the failure mode of the rock under the action of load;
(3) The invention can realize more accurate discrimination of rock damage modes, has wide application range, is suitable for discrimination of damage modes when different geological causes and different kinds of rocks are damaged under the action of load, and can accurately provide quantitative evaluation of damage modes in each damage stage in the whole rock damage process.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a diagram of acoustic emission sensor location installation under uniaxial compression;
FIG. 3 is an acoustic emission waveform diagram of an original acoustic emission signal after passing through a wavelet threshold denoising method;
FIG. 4 is a two-dimensional spectrum obtained by fast Fourier transform of a certain denoised transmit signal;
FIG. 5 is a graph of frequency domain information processing ambiguity I spectrum for a certain denoised transmit signal;
FIG. 6 is a diagram of a frequency domain information processing process of a denoised transmit signal as a blurred II spectrum;
FIG. 7 is a diagram of a primary frequency, secondary primary frequency capture and identification process for a certain denoised transmit signal;
FIG. 8 is a diagram of primary and secondary primary frequency rasterization capture of a primary and secondary primary frequency capture identification process for a particular denoised transmit signal;
fig. 9 is a two-dimensional spectrum diagram of an H-H type signal (dual high frequency signal);
FIG. 10 is a two-dimensional spectrum of an L-L type signal (dual high frequency signal);
FIG. 11 is a two-dimensional spectrum of an H-L type signal (mixed frequency signal type I);
FIG. 12 is a two-dimensional spectrum of an H-L type signal (mixed frequency signal type II);
FIG. 13 is a plot of the center frequency of the acoustic emission of granite versus load for example 2;
FIG. 14 is a plot of the primary-secondary frequency center frequency versus load of the sandstone acoustic emissions of example 2;
fig. 15 is a plot of primary-secondary frequency center frequency versus load for the marble acoustic emissions of example 2.
Detailed Description
The invention will be described in further detail with reference to specific embodiments, but the scope of the invention is not limited to the description.
Example 1: as shown in FIG. 1, the rock destruction acoustic emission secondary main frequency identification extraction method specifically comprises the following steps:
(1) Rock of different geological origin was prepared as standard cylinder samples:
the rock with different geological causes comprises magma rock, sedimentary rock and metamorphic rock, granite is used as a magma rock sample, sandstone is used as a sedimentary rock sample, and marble is used as a metamorphic rock sample;
the size of the sample is a standard cylinder with the diameter phi 50mm multiplied by the height H100 mm; the non-parallelism error of the two end surfaces of the sample is less than 0.05mm; the two end faces of the sample are perpendicular to the axis, and the deviation is smaller than 0.25 degrees; the error of the diameter of the sample along the height is less than 0.3mm;
(2) Acoustic emission sensors are uniformly arranged on the side surface of the cylindrical sample along the circumferential direction (see fig. 2);
the acoustic emission sensor on the side surface of the cylinder sample is axially arranged with upper and lower layers 2 layers along the cylinder sample, the distance between the acoustic emission sensor on the upper layer and the top end of the cylinder sample is 1/8-3/8 of the height of the cylinder sample, and the distance between the acoustic emission sensor on the lower layer and the bottom end of the cylinder sample is 1/8-3/8 of the height of the cylinder sample; preferably, the number of the acoustic emission sensors is 8, the number of the acoustic emission sensors on the upper layer is 4, the distance between the acoustic emission sensors on the upper layer and the top end of the cylindrical sample is 1/4 of the height of the cylindrical sample, and the distance between the acoustic emission sensors on the lower layer and the bottom end of the cylindrical sample is 1/4 of the height of the cylindrical sample;
(3) Carrying out a uniaxial compression experiment on a cylindrical sample by adopting a rock mechanical testing machine, wherein an acoustic emission sensor receives an original acoustic emission waveform which is released when the rock sample starts to be loaded to be completely destroyed in the whole process in the experimental process;
firstly, applying a load of 0.5kN to a sample, and after the pressure-bearing end of the sample is fully contacted with a press, synchronizing the sampling time of a rock mechanical testing machine and an acoustic emission signal acquisition system, and continuously applying an axial load at a rate of 0.2mm/min until the sample is completely destroyed; the acoustic emission signal acquisition system sets sampling frequency: 1000kHz, sample length: 2048, threshold: 40dB, gain of forward: 40dB;
(4) Denoising an original acoustic emission waveform, wherein a db3 wavelet basis is selected by a wavelet threshold denoising method, and a soft threshold function and a rigrsure threshold rule are adopted; then performing fast Fourier transform to obtain a two-dimensional spectrogram; the two-dimensional spectrum information after the fast Fourier transform is
S 0 ＝[(f 1 ,a 1 ),(f 2 ,a 2 ),…,(f p ,a p ),…,(f n ,a n )]
Wherein: s is S 0 -spectral information, f-nyquist frequency, a-amplitude, p-peak point, n-frequency domain data total;
(5) Carrying out blurring processing on amplitude and frequency data in the two-dimensional spectrogram to obtain a blurring two-dimensional spectrogram;
the blurring processing method comprises the following steps of
1) S is selected 0 The medium amplitude value simultaneously satisfies a p ＞a p-1 And a p ＜a p+1 Peak point (f) of (p.gtoreq.2) condition p ,a p ) Sequentially store S 1 Through S 1 Mapping to obtain a blurred I spectrum diagram
Wherein: s is S 1 -blurring of i spectral information, f p -blurring of I peak frequency, a p -blur i peak amplitude, p-blur i peak, n-blur i frequency domain data total.
2) S is selected 1 The medium amplitude value simultaneously satisfies a p ＞a p-1 And a p ＜a p+1 Peak point (f) of (p.gtoreq.2) condition p ,a p ) Sequentially store S 2 Through S 2 Drawing to obtain a fuzzy II spectrogram
Wherein: s is S 2 -blurring of ii spectral information, f pp -fuzzification of the peak frequency, a, of the ii pp -peak amplitude of fuzzification ii, peak of p-fuzzification ii, total number of n-fuzzification ii frequency domain data.
(6) Capturing and identifying an acoustic emission signal with a secondary primary frequency characteristic, and extracting an acoustic emission primary frequency and a secondary primary frequency of the acoustic emission signal; the primary frequency and secondary primary frequency characteristic identification and extraction method comprises the following steps of
1) Determining peak searching criterion, i.e. capturing peak value and peak position, searching mutually independent peak points in the blurred II spectrogram, and determining peak value and peak position point (f ppp ,a ppp ) Deposit S 3 ；
2) Through S 3 Drawing a rasterized extremum diagram by medium data, selecting a peak position corresponding to the highest peak value and a peak position corresponding to the next highest peak value in the rasterized extremum diagram, and calculating a ratio R of the next highest peak value to the highest peak value
Wherein: a, a sub-max Sub-peak amplitude, a max -a highest peak amplitude;
3) If R is less than 80%, the signal is marked as a signal without secondary main frequency characteristics, and can not be used for judging the rock destruction mode; if R is greater than 80%, the highest peak amplitude in the grid extremum chart is marked as the main frequency amplitude of the acoustic emission signal, and the frequency corresponding to the highest peak amplitude is the main frequency of the signal; the secondary peak amplitude is the secondary main frequency amplitude of the signal, and the frequency corresponding to the secondary peak amplitude is the secondary main frequency of the signal;
(7) Acquiring acoustic emission signals of different lithology samples from the beginning of loading to the complete destruction of the whole process, obtaining acoustic emission signal frequency domain data of each moment of rock damage destruction, judging the type of the acoustic emission signals according to the distribution characteristics of the main frequency and the secondary main frequency of the acoustic emission signals with the characteristic of the secondary main frequency, calculating the center frequency of each type of signals, and describing the destruction mode of the whole rock destruction process by combining the sample destruction load-time curve;
method for judging type and destruction mode of acoustic emission signal
1) For the acoustic emission signal with the secondary primary frequency characteristic, calculating a frequency interval formed by the primary frequency and the secondary primary frequency value of the acoustic emission signal;
2) Dividing the frequency interval into two equal parts by utilizing a frequency dividing line, wherein the frequency at the dividing line is defined as the frequency of the dividing line;
3) The signals with the primary frequency and the secondary primary frequency not smaller than the boundary frequency are regarded as H-H type double high frequency signals, the signals with the primary frequency and the secondary primary frequency smaller than the boundary frequency are regarded as L-L type double low frequency signals, and the signals with the primary frequency larger than the boundary frequency and the secondary primary frequency smaller than the boundary frequency or the signals with the primary frequency smaller than the boundary frequency and the secondary primary frequency larger than the boundary frequency are regarded as H-L type mixed frequency signals;
4) The double high frequency signals correspond to shear damage, the double low frequency signals correspond to stretch-draw damage, and the mixed frequency signals correspond to stretch-shear composite damage;
5) The center frequencies of the H-H type signal, the L-L type signal and the H-L type signal are calculated respectively, the damage evolution process (sample damage time-load curve) of the whole loading process of each rock sample is divided into 3 stages according to the axial stress-strain relation of each rock sample, the stages are compaction to elastic deformation stage (stage I), micro-crack stable development stage (stage II) and crack expansion to damage stage (stage III) in sequence, and the damage mode of the whole rock damage process is described by combining the sample damage load-time curve.
Example 2: as shown in FIG. 1, the rock destruction acoustic emission secondary main frequency identification extraction method specifically comprises the following steps:
s1, preparing rocks with different geological factors into standard cylinder samples; rock can be divided into magma rock, sedimentary rock and metamorphic rock according to geological causes, wherein granite is selected as a magma rock sample, the serial number is Gra group, sandstone is a sedimentary rock sample, the serial number is San group, marble is metamorphic rock sample, the serial number is Mar group, granite, sandstone and marble producing areas are Hunan Yue Yang, sichuan Yue Yang and Hunan Yue Yang respectively; the standard cylinder sample with the diameter phi of 50mm and the height H of 100mm is prepared by unified finish machining in a laboratory through equipment such as a vertical coring machine, a rock cutting machine, a double-end-face grindstone machine and the like; the non-parallelism error of the two end surfaces of the sample is less than 0.05mm; the two end faces of the sample are perpendicular to the axis, and the deviation is smaller than 0.25 degrees; the error of the diameter of the sample along the height is less than 0.3mm;
s2, arranging an acoustic emission sensor on the side surface of the prepared cylinder sample, and smearing high-vacuum silicone grease between the sensor and the contact surface of the sample; the acoustic emission sensors are of the type SR-150M, the center frequency is 150kHz, the number of the acoustic emission sensors is 8, the acoustic emission sensors are sequentially arranged at the position 25mm away from the upper end surface (upper layer surface) of the sample and the position 25mm away from the lower end surface (lower layer surface) of the sample, the number of the acoustic emission sensors is 4 on the same layer, and the adjacent sensors are spaced by 90 degrees, so that the integral monitoring of the rock sample can be better realized, and the rock sample is shown in the figure 2;
s3, carrying out a uniaxial compression experiment on the cylindrical sample by using a rock mechanical testing machine, and receiving an original acoustic emission waveform from the beginning of loading the rock sample to the complete destruction of the whole process release by using an acoustic emission sensor: placing the rock sample which is completely distributed by the acoustic emission sensor in the step S2 in the center of an axial bearing plate of a microcomputer-controlled electrohydraulic servo rock testing machine, taking a pencil lead breaking signal with the diameter phi of 0.3mm and the hardness of 2H as an analog source, breaking the pencil lead at an angle of about 2.5mm with the side surface of the sample for more than 3 times at any position between the acoustic emission upper-layer sensor and the acoustic emission lower-layer sensor of the sample, taking an average value of more than 3 times of response amplitude values, and checking the sensitivity of each channel by taking the difference between the amplitude value of the response of a single channel and the average amplitude value of all channels to be not more than +/-4 dB; after the test is finished, operating a rock mechanical testing machine loading system, operating an acoustic emission signal acquisition system by another experimenter, applying 0.5kN load to a sample in advance by adopting an axial displacement closed-loop control mode, synchronizing the sampling time of the rock mechanical testing machine loading system and the acoustic emission signal acquisition system after the pressure-bearing end of the sample is fully contacted with a press, starting the mechanical loading system and the acoustic emission acquisition system, continuing to apply the axial load at the speed of 0.2mm/min until the sample is completely destroyed, stopping the two systems at the same time, and storing test data; the acoustic emission signal acquisition system sets sampling frequency: 1000kHz, sample length: 2048, threshold: 40dB, gain of forward: 40dB;
s4, denoising the original acoustic emission waveform of the rock sample loaded to the whole damage process; taking the 7776 th (No. 7776) acoustic emission waveform of a marble Mar-1 sample as an example, selecting db3 of Daubechies wavelet family with good regularity and tight support as a wavelet base, and describing a wavelet threshold denoising process by adopting a soft threshold function and a rigrsure threshold rule, wherein the wavelet threshold denoising process is shown in figure 3; the application method of the rigrsure threshold rule and the soft threshold function comprises the following steps:
(1) Let the vector W be the square of the wavelet transform coefficient of the detected signal, and arrange in order from small to large, there are:
W＝[w 1 ,w 2 ,...,w N ](w 1 ≤w 2 ≤...≤w N )
wherein: the square of the wavelet transform coefficient of the w-detected signal; n is the length of the detected signal;
(2) Let the risk vector R, its element R i The method comprises the following steps:
wherein: i=1, 2,. -%, N;
(3) With the smallest element R in the risk vector R min As a risk value, a corresponding w is found i Calculating a rigrsure threshold:
wherein: lambda-rigrsure threshold, sigma-noise strength, w i -a corresponding w value of the risk value;
(4) The square value of the wavelet coefficient is processed by adopting a soft threshold function:
wherein: sign-sign function; w (w) s -denoised values;
s5, performing fast Fourier transform on the denoised No.7776 waveform by using an acoustic emission spectrum analysis system to obtain a two-dimensional spectrogram, as shown in FIG. 4; the Nyquist sampling theorem is adopted, and two-dimensional spectrum information consists of two columns of elements, namely 1024 groups;
S 0 ＝[(f 1 ,a 1 ),(f 2 ,a 2 ),…,(f p ,a p ),…,(f 1024 ,a 1024 )]
wherein: s is S 0 -spectral information, f-nyquist frequency, a-amplitude, p-peak point;
s6, blurring processing is carried out on amplitude and frequency data in the two-dimensional spectrogram, and a blurred two-dimensional spectrogram is drawn; the two-dimensional spectrogram blurring processing method comprises the following steps:
(1) S is selected 0 The medium amplitude value simultaneously satisfies a p ＞a p-1 And a p ＜a p+1 Peak spectral data point (f) for (p.gtoreq.2) condition p ,a p ) 264 groups are sequentially stored in S 1 Through S 1 Drawing to obtain a fuzzy I-frequency spectrogram, as shown in FIG. 5;
wherein: s is S 1 -blurring of i spectral information, f p -blurring of I peak frequency, a p -blurring i peak amplitude, p-blurring i peak;
(2) Then using the same method to select S 1 The frequency spectrum data points meeting the condition are 87 groups and are sequentially stored in S 2 Then through S 2 Drawing to obtain a fuzzy II spectrogram, as shown in FIG. 6;
wherein: s is S 2 -blurring of ii spectral information, f pp -fuzzification of the peak frequency, a, of the ii pp -blur ii peak amplitude, p-blur ii peak.
S7, capturing and identifying an acoustic emission signal with a secondary primary frequency characteristic, and extracting an acoustic emission primary frequency and a secondary primary frequency; the specific method comprises the following steps:
(1) Determining peak-finding criteria, i.e. capturing peak value (amplitude) and peak position (frequency), searching fuzzified II spectrogramIn (1) (see FIG. 7), 26 groups of peaks and peak sites (f) ppp ,a ppp ) Deposit S 3 ；
(2) Through S 3 Drawing a rasterization extremum diagram by medium data, setting the grid interval to be 2kHz, selecting a peak position corresponding to the highest peak value and a peak position corresponding to the next highest peak value in the rasterization extremum diagram (see figure 8), and calculating a ratio R of the next highest peak value to the highest peak value;
wherein: a, a sub-max -sub-peak amplitude;
a max -a highest peak amplitude;
(3) If R is less than 80%, the signals are marked as signals without secondary main frequency characteristics, and the signals cannot be used for judging the rock destruction mode; if R is greater than 80%, the highest peak amplitude in the grid extremum chart is marked as the main frequency amplitude of the acoustic emission signal; the frequency corresponding to the highest peak amplitude is the main frequency of the signal; the secondary peak amplitude is the secondary main frequency amplitude of the signal; the frequency corresponding to the amplitude of the secondary peak is the secondary main frequency of the signal, the main frequency of the No.7776 waveform is 55.66kHz, the amplitude of the main frequency is 1.36V, the amplitude of the secondary main frequency is 169.43kHz, and the amplitude of the secondary main frequency is 1.13V;
s8, acquiring acoustic emission signals of granite, sandstone and marble samples from the beginning of loading to the complete destruction of the whole process, and obtaining acoustic emission signal frequency domain data of each moment of rock damage and destruction; for the acoustic emission signal with the secondary primary frequency characteristic, calculating a frequency interval formed by the primary frequency and the secondary primary frequency value of the acoustic emission signal; dividing the frequency interval into two equal parts by utilizing a frequency dividing line, defining the frequency at the dividing line as a boundary frequency, regarding a signal with a main frequency and a secondary main frequency which are not less than the boundary frequency as an H-H type double high frequency signal (see fig. 9), regarding a signal with a main frequency and a secondary main frequency which are less than the boundary frequency as an L-L type double low frequency signal (see fig. 10), regarding a signal with a main frequency which is greater than the boundary frequency and a secondary main frequency which is less than the boundary frequency (see fig. 11) or regarding a signal with a main frequency which is less than the boundary frequency and a secondary main frequency which is greater than the boundary frequency as an H-L type double low frequency signal (see fig. 12); the double high frequency signals correspond to shear damage, the double low frequency signals correspond to stretch-draw damage, and the mixed frequency signals correspond to stretch-shear composite damage;
calculating the center frequencies of an H-H type signal, an L-L type signal and an H-L type signal respectively, dividing the damage evolution process (sample breaking time-load curve) of the whole loading process of each rock sample into 3 stages according to the axial stress-strain relation of each rock sample, and describing the breaking mode of the whole rock breaking process by combining the sample breaking load-time curve, wherein the stages comprise a compaction stage (stage I) to an elastic deformation stage (stage II) and a crack expansion stage (stage III) in sequence;
a granite acoustic emission center frequency and load relation curve is shown in fig. 13; in the stage I, the original defects and micro cracks in the granite are compacted and closed, a small amount of penetration is generated, the micro cracks correspond to tension fracture, the newly initiated micro cracks are fewer and correspond to shear fracture, so that the number of signals representing the tension fracture is more than that of signals representing the shear fracture, and a certain number of signals representing the tension-shear composite fracture are released due to hardening of the sample in the stage I; with the increase of the test load, the granite damage evolution process enters a stage II, the compaction closing process of the original defects and the microcracks of the sample is finished, the newly inoculated microcracks are rapidly increased, the microcracks are stably developed, signals representing the shearing damage begin to gather and reproduce, and signals representing the tension-shear composite damage are obviously more than those of the stage I; with further increase of test load, the granite damage evolution process enters a stage III, the sample shows progressive degradation behavior, the micro-cracks formed in the sample are expanded and penetrated under the action of high stress state and are interacted with the newly inoculated micro-cracks, and the sample gradually approaches to a macroscopic fracture surface, so that shearing damage, tensioning damage and tension-shear composite damage are rapidly developed, and a large number of signals representing the shearing damage, tensioning damage and tension-shear composite damage are generated before the granite is nearly completely damaged;
the sandstone acoustic emission center frequency and load relationship curve is shown in fig. 14; in the stage I, the sandstone contains more holes, so that the deformation of a sample under the action of low load is mainly compact in the compression of the holes, and the number of newly-initiated fracture sources is very small, so that only tension fracture and trace tension-shear composite fracture occur at the initial stage of the test, and no shear fracture occurs, and therefore, only signals representing the tension-tension fracture and scattered signals representing the tension-shear composite fracture exist at the stage; after the sandstone damage evolution process enters a stage II, the compaction and compaction process of the primary holes in the sample is ended, the primary holes gradually transform to the initiation development of new microcracks, and a tension-shear composite damage mode begins to appear, so that signals representing tension-shear composite damage in the stage are largely emerging; under the continuous action of load, the sandstone damage evolution process enters a stage III, the interaction of formed adjacent microcracks becomes more prominent, so that the samples are subjected to shear damage, the shear damage signals are generated for the first time in the whole test process, particularly when the samples are close to complete damage, the tension damage, the shear damage and the tension-shear composite damage signals are simultaneously generated, and the fact that the combined action of 3 damage modes causes the complete damage of sandstone is shown;
the relation curve of the acoustic emission center frequency and the load of the marble is shown in fig. 15; in the stage I, the marble generates a vertical crack group in a local initial state in the elastic deformation process of the sample at the initial stage of the test due to the hard brittleness of the marble, and is simultaneously mixed with a certain amount of tension-shear composite damage, which corresponds to a signal representing the tension damage and a signal representing the tension-shear composite damage; in the stage II, the elastic deformation process of the marble is finished, the vertical crack group formed in the sample is subjected to shearing damage for the first time while the vertical crack group is stably developed, and a frequency band continuously evolving along with time is gradually formed corresponding to a signal representing the shearing damage; in the stage III, when the shearing cracks, the stretch-draw cracks and the stretch-shear compound cracks which are formed in the marble reach enough quantity, the damage of the sample is changed by the quantity, the cracks are mutually expanded, communicated and even broken in the stage, and a plurality of damage modes jointly occur and jointly act, so that the plastic damage of the sample is aggravated, the frequency range of the signal representing the stretch-shear compound damage is widened, and the quantity of the signals representing the stretch-draw damage and the shear damage is obviously increased.
The embodiment is characterized in that based on acoustic emission frequency domain information, an acoustic emission secondary main frequency identification extraction method is utilized for rock damage, acoustic emission signals of main frequencies and secondary main frequencies of different lithology rocks exist simultaneously in the damage process, and the damage mode and crack morphology of the rocks under the uniaxial compression condition are further disclosed.
While the present invention has been described in detail with reference to the drawings, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art.
Claims (4)
1. A rock destruction acoustic emission secondary main frequency identification extraction method is characterized by comprising the following specific steps:
(1) Preparing rocks with different geological factors into standard cylinder samples;
(2) Acoustic emission sensors are uniformly arranged on the side surface of the cylindrical sample along the circumferential direction;
(3) Carrying out a uniaxial compression experiment on a cylindrical sample by adopting a rock mechanical testing machine, wherein an acoustic emission sensor receives an original acoustic emission waveform which is released when the rock sample starts to be loaded to be completely destroyed in the whole process in the experimental process;
(4) Denoising the original acoustic emission waveform, and then performing fast Fourier transform to obtain a two-dimensional spectrogram; the denoising process is a wavelet threshold denoising method, wherein the wavelet threshold denoising method selects db3 wavelet basis and adopts soft threshold function and rigrsure threshold rule;
the two-dimensional spectrum information after the fast Fourier transform is:
；
wherein:-spectral information->-nyquist frequency, ">Amplitude, & gt>Peak point,/->-a total number of frequency domain data;
(5) Carrying out blurring processing on amplitude and frequency data in the two-dimensional spectrogram to obtain a blurred two-dimensional spectrogram;
the blurring processing method comprises the following steps:
1) SelectingThe middle amplitude value satisfies +.>And->And->Peak point of condition->Sequentially depositBy->Mapping to obtain a blurred I spectrum diagram
；
Wherein:-blurring of i spectral information,/->-blurring the peak frequency of I, < >>-blurring peak amplitude of i>-blurring of peak i,/->-blurring the total number of i frequency domain data;
2) SelectingThe middle amplitude value satisfies +.>And->And->Peak point of condition->Sequentially depositBy->Drawing to obtain a fuzzy II spectrogram
；
Wherein:-blurring ii spectral information,/->-blurring peak frequency of ii->-blurring peak amplitude of ii,>-blurring peak ii,>-blurring the sum of ii frequency domain data;
(6) Capturing and identifying an acoustic emission signal with a secondary primary frequency characteristic, and extracting an acoustic emission primary frequency and a secondary primary frequency of the acoustic emission signal;
the primary frequency and secondary primary frequency characteristic identification and extraction method comprises the following steps:
1) Determining peak searching criteria, namely capturing peak value and peak position, searching mutually independent peak points in the fuzzy II-frequency spectrogram, and obtaining peak value and peak position pointStore->；
2) By passing throughDrawing a rasterized extremum diagram by medium data, selecting a peak position corresponding to the highest peak value and a peak position corresponding to the next highest peak value in the rasterized extremum diagram, and calculating the ratio of the next highest peak value to the highest peak value +.>；
；
Wherein:-blurring iii spectral information,/->-sub-peak amplitude, < >>-a highest peak amplitude;
3) If it isIf the frequency is less than 80%, the signal is marked as a signal without secondary main frequency characteristics, and can not be used for judging the rock destruction mode; if->If the frequency is more than 80%, the highest peak amplitude in the grid extremum chart is marked as the main frequency amplitude of the acoustic emission signal, and the frequency corresponding to the highest peak amplitude is the main frequency of the signal; the secondary peak amplitude is the secondary main frequency amplitude of the signal, and the frequency corresponding to the secondary peak amplitude is the secondary main frequency of the signal;
(7) Acquiring acoustic emission signals of different lithology samples from the beginning of loading to the complete destruction of the whole process, obtaining acoustic emission signal frequency domain data of each moment of rock damage destruction, judging the type of the acoustic emission signals according to the distribution characteristics of the main frequency and the secondary main frequency of the acoustic emission signals with the characteristic of the secondary main frequency, calculating the center frequency of each type of signals, and describing the destruction mode of the whole rock destruction process by combining the sample destruction load-time curve;
the judging method of the type and the destruction mode of the acoustic emission signal comprises the following steps:
1) For the acoustic emission signal with the secondary primary frequency characteristic, calculating a frequency interval formed by the primary frequency and the secondary primary frequency value of the acoustic emission signal;
2) Dividing the frequency interval into two equal parts by utilizing a frequency dividing line, wherein the frequency at the dividing line is defined as the frequency of the dividing line;
3) The signals with the primary frequency and the secondary primary frequency not smaller than the boundary frequency are regarded as H-H type double high frequency signals, the signals with the primary frequency and the secondary primary frequency smaller than the boundary frequency are regarded as L-L type double low frequency signals, and the signals with the primary frequency larger than the boundary frequency and the secondary primary frequency smaller than the boundary frequency or the signals with the primary frequency smaller than the boundary frequency and the secondary primary frequency larger than the boundary frequency are regarded as H-L type mixed frequency signals;
4) The double high frequency signals correspond to shear damage, the double low frequency signals correspond to stretch-draw damage, and the mixed frequency signals correspond to stretch-shear composite damage;
5) The center frequencies of the H-H type signal, the L-L type signal and the H-L type signal are respectively calculated, the damage evolution process of the whole loading process of each rock sample is divided into 3 stages according to the axial stress-strain relation of each rock sample, the stages from compaction to elastic deformation are sequentially carried out, namely, stage I, the stable development stage of micro cracks is carried out, namely, stage II, and the crack is expanded to a breaking stage, namely, stage III, and the breaking mode of the whole rock breaking process is described by combining the sample breaking load-time curve.
2. The rock destruction acoustic emission secondary dominant frequency identification extraction method according to claim 1, wherein: the rock with different geological factors in the step (1) comprises magma rock, sedimentary rock and metamorphic rock, granite is used as a magma rock sample, sandstone is used as a sedimentary rock sample, and marble is used as a metamorphic rock sample.
3. The rock destruction acoustic emission secondary dominant frequency identification extraction method according to claim 1, wherein: and (2) arranging an acoustic emission sensor on the side surface of the cylindrical sample in an upper layer and a lower layer along the axial direction of the cylindrical sample, wherein the distance between the acoustic emission sensor on the upper layer and the top end of the cylindrical sample is 1/8~3/8 of the height of the cylindrical sample, and the distance between the acoustic emission sensor on the lower layer and the bottom end of the cylindrical sample is 1/8~3/8 of the height of the cylindrical sample.
4. The rock destruction acoustic emission secondary dominant frequency identification extraction method according to claim 1, wherein: the loading mode of the uniaxial compression experiment in the step (3) is axial displacement closed-loop control.
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